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Tanner Schmidt
Tanner Schmidt
Meta Reality Labs
Bestätigte E-Mail-Adresse bei meta.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Y Xiang, T Schmidt, V Narayanan, D Fox
arXiv preprint arXiv:1711.00199, 2017
20382017
Deep local shapes: Learning local sdf priors for detailed 3d reconstruction
R Chabra, JE Lenssen, E Ilg, T Schmidt, J Straub, S Lovegrove, ...
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
4392020
Neural 3d video synthesis from multi-view video
T Li, M Slavcheva, M Zollhoefer, S Green, C Lassner, C Kim, T Schmidt, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
3032022
Self-supervised visual descriptor learning for dense correspondence
T Schmidt, R Newcombe, D Fox
IEEE Robotics and Automation Letters 2 (2), 420-427, 2016
1802016
DART: Dense Articulated Real-Time Tracking.
T Schmidt, RA Newcombe, D Fox
Robotics: Science and systems 2 (1), 1-9, 2014
1622014
Star: Self-supervised tracking and reconstruction of rigid objects in motion with neural rendering
W Yuan, Z Lv, T Schmidt, S Lovegrove
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
922021
Frodo: From detections to 3d objects
M Runz, K Li, M Tang, L Ma, C Kong, T Schmidt, I Reid, L Agapito, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
82*2020
Depth-based tracking with physical constraints for robot manipulation
T Schmidt, K Hertkorn, R Newcombe, Z Marton, M Suppa, D Fox
2015 IEEE International Conference on Robotics and Automation (ICRA), 119-126, 2015
792015
DART: dense articulated real-time tracking with consumer depth cameras
T Schmidt, R Newcombe, D Fox
Autonomous Robots 39, 239-258, 2015
682015
Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes. arXiv 2017
Y Xiang, T Schmidt, V Narayanan, D Fox
arXiv preprint arXiv:1711.00199, 0
68
Algorithm-aware neural network based image compression for high-speed imaging
R Pinkham, T Schmidt, A Berkovich
2020 IEEE International Conference on Artificial Intelligence and Virtual …, 2020
142020
Dynamic high resolution deformable articulated tracking
A Walsman, W Wan, T Schmidt, D Fox
2017 International Conference on 3D Vision (3DV), 38-47, 2017
112017
Neural 3D Video Synthesis
Z Lv, M Slavcheva, T Li, M Zollhoefer, SG Green, T Schmidt, M Goesele, ...
US Patent App. 17/571,285, 2022
52022
Feature query networks: Neural surface description for camera pose refinement
H Germain, D DeTone, G Pascoe, T Schmidt, D Novotny, R Newcombe, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
52022
Dynamically programmable image sensor
AS Berkovich, R Pinkham, T Schmidt
US Patent App. 16/983,863, 2021
42021
Self-directed lifelong learning for robot vision
T Schmidt, D Fox
Robotics Research: The 18th International Symposium ISRR, 109-114, 2019
42019
Identity-disentangled neural deformation model for dynamic meshes
B Xu, L Ma, Y Ye, T Schmidt, CD Twigg, S Lovegrove
arXiv preprint arXiv:2109.15299, 2021
22021
Explicit Radiance Field Reconstruction from Scratch
S Aroudj, M Goesele, RA Newcombe, T Schmidt, FER Ilg, SJ Lovegrove
US Patent App. 18/160,937, 2023
12023
ERF: Explicit Radiance Field Reconstruction From Scratch
S Aroudj, S Lovegrove, E Ilg, T Schmidt, M Goesele, R Newcombe
arXiv preprint arXiv:2203.00051, 2022
2022
A Paradigm Shift in Tissue Engineering: From a Top–Down to a Bottom–Up Strategy. Processes 2021, 9, 935
T Schmidt, Y Xiang, X Bao, T Sun
s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021
2021
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